Comparative metabolomics study on the secondary metabolites of the red alga, Corallina officinalis and its associated endosymbiotic fungi

Marine endosymbionts have gained remarkable interest in the last three decades in terms of natural products (NPs) isolated thereof, emphasizing the chemical correlations with those isolated from the host marine organism. The current study aimed to conduct comparative metabolic profiling of the marine red algae Corallina officinalis, and three fungal endosymbionts isolated from its inner tissues namely, Aspergillus nidulans, A. flavipes and A. flavus. The ethyl acetate (EtOAc) extracts of the host organism as well as the isolated endosymbionts were analyzed using ultra-high performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-MS/MS)in both positive and negative ion modes, applying both full scan (FS) and all ion fragmentation (AIF) modes. Extensive interpretation of the LC-MS/MS spectra had led to the identification of 76 metabolites belonging to different phytochemical classes including alkaloids, polyketides, sesquiterpenes, butyrolactones, peptides, fatty acids, isocoumarins, quinones, among others. Metabolites were tentatively identified by comparing the accurate mass and fragmentation pattern with metabolites previously reported in the literature, as well as bioinformatics analysis using GNPS. A relationship between the host C. officinalis and its endophytes (A. flavus, A. nidulans, and A. flavipes) was discovered. C. officinalis shares common metabolites with at least one of the three endosymbiotic fungi. Some metabolites have been identified in endophytes and do not exist in their host. Multivariate analysis (MVA) revealed discrimination of A. flavipes from Corallina officinalis and other associated endophytic Aspergillus fungi (A. flavus and A. nidulans).


Introduction
The expanding number of marine-derived natural products described from endosymbiotic fungi encourages additional action and in-depth research for marine environment-derived natural bioactive compounds from a drug discovery perspective. 1,2Macroalgae are divided into three primary phyla based on their coloration, which includes red seaweed (Rhodophyta), brown seaweed (Phaeophyta), and green seaweed (Chlorophyta). 3 Corallina officinalis, a red seaweed, has a long history of use in traditional Chinese medicine and is a wellknown edible seaweed in China and many other nations. 4ed algae are known to contain a variety of secondary metabolites, including sulfated sugars, halogenated mono-and diterpenes, sterols, alkaloids, and polyphenols.Many reports demonstrated the biological impact of the secondary metabolites isolated from genus Corallina and the endophytes isolated thereof; for example, The in vitro assay of total extract of C. officinalis exhibited antiprotozoal activity against Trypanosoma cruzi. 5The new cyclic depsipeptides isolated from culture broth of Staphylococcus sp.derived from C. officinalis, known as cyclo (2a, 3-diamino-propoincacid-L-Asn-3-b-hydroxy-5-methyl-tetradecanoicacid-L-Leu1-L-Asp-L-Val-L-Leu2-L-Leu3) and cyclo(L-pro-vast classes of chemical compounds with interesting biological functions.[10][11][12][13][14] Recently, metabolomic studies became an indispensable tool in natural products chemistry where it provides broad qualitative and quantitative proles of metabolites in organisms under diverse environmental situations.Under stressful circumstances, both plants and microbes create a wide variety of metabolites with distinct chemistries and bioactivities.Through integrated sowares, platforms, libraries and databases it is possible to unveil the intricate interactions between endophytes and their host organisms. 15PLC/MS/MS provides a highly sensitive and adaptable tool and represents the basic tool in metabolomic studies with the ability to analyze minor chemicals providing crucial structural information for identication.However, massive volumes of spectra may be produced using mass spectrometry, which increases the complexity of the analysis.Considering that, the online platform Global Natural Products Social Molecular Networking (GNPS) allows the use of several different mass spectrometry-based metabolomics tools to analyze large sets of data.Moreover, numerous tools offered by GNPS have the ability to automatically search for a spectral match, and the organization provides a public spectrum library. 16,17inding a link between the secondary metabolites produced by the host organism and those produced by the endophytic community is essential to unveil the ecological signicance of endophytes and to open new avenue to discover the need of such mutualistic relationship.
In the present study and in continuation of our ongoing research on marine endosymbiotic fungal products, we herein report a comparative LC-MS-MS metabolomics study on the ethyl acetate extracts of the red algae C. officinalis and three endosymbiotic fungi isolated from its inner tissue namely; A. nidulans, A. avipes and A. avus.The identied metabolites belonged to various chemical classes such as alkaloids, anthraquinones, polyketides, sesquiterpenes, butyrolactones, peptides, fatty acids, isocoumarins, quinones, among other miscellaneous compounds.

Fungal material
The fungi A. nidulans, A. avipes and A. avus were isolated from the inner tissues of the red algae C. officinalis.The algae was collected in the Mediterranean Sea close to Alexanderia, Egypt, in September 2018.For isolation of the fungal strain, the Algae was rinsed with distilled water and then surface sterilization using 70% ethanol was performed for 2 min.Small samples from the inner tissues of the algae were aseptically cut using sterilized blade and pressed onto malt agar plate (15 g per L malt extract, 15 g per L agar, 0.2 g per L chloramphenicol to suppress bacterial growth, pH adjusted to 7.4-7.8using 10% NaOH).Aer incubation at 25 °C the fungal strains under investigation were found to grow out of the algal tissue.Pure fungal strains were grown by repeated reinoculation on fresh culture media.

Identication of the fungal strains
The isolated fungal strains were identied as A. nidulans, A. avipes and A. avus using a molecular biological protocol by DNA amplication and sequencing of the ITS region as previously reported. 18The obtained data of sequencing were submitted to GenBank with the accession number OQ930448 for A. nidulans, OQ930542 for A. avipes and OR120990 for A. avus.

Cultivation and extraction
Small scale fermentation of the fungal strains was performed on solid rice culture media (100 g rice in 110 mL distilled water, autoclaved for 20 min at 121 °C) in 1 L Erlenmeyer ask (3 asks) for 30 days at 25 °C under static conditions.Aer incubation, the fungal cultures were extracted with ethyl acetate, ltered, and evaporated with a rotary evaporator to yield the ethyl acetate extracts for A. nidulans (350 mg), A. avipes (400 mg) and A. avus (500 mg).Similarly, the algae for C. officinalis was extracted and evaporated to yield 400 mg total extract.Aliquots (10 mg) of each extraction was dissolved in 1 ml of 50% methanol per water, centrifuged at 14 000 rpm for 5 min and ltered through nylon syringe lters (0.22 mm) before subjected to further analysis.

Ultra-performance liquid chromatography (UPLC) analysis
The metabolites of the extracts were analyzed on a reversed phase C18 column (High Strength Silica (HSS) T3, 100 mm × 2.1 mm, 1.7 mm diameter particles, Waters™, Waters Corporation, Milford, MA 01757, USA), connected to ultraperformance liquid chromatography (LC) system (Waters™ Acquity UPLC system, Waters Corporation, Milford, MA 01757, USA). 16The injection volume was four mL and the ow rate was adjusted to 400 mL min −1 .The mobile phases used for chromatographic separation were water containing 0.1% formic acid (A) and acetonitrile containing 0.1% formic acid (B).The following gradient was applied: 1 min 99% A, 13 min linear gradient from 99% A to 45% A, 14.5 min linear gradient from 45% A to 30% A, 15.5 min linear gradient from 30% A to 1% A. The gradient was hold at 1% A from 15.5 to 17 min, followed by linear gradient from 1% A to 99% A to 17.5 min.Finally, the column was re-equilibrated for 2.5 min at 99% A.

High-resolution electrospray ionisation orbitrap mass spectrometry (HR-ESI-orbitrap-MS) analysis
The mass spectra were acquired, covering a mass range 100-1500 m/z, by orbitrap-type high resolution MS and MS/MS (Thermo Scientic™ Exactive™, Thermo Fisher, Bremen, Germany). 19Collision Induced Dissociation (CID) was obtained using a normalized collision energy of 35 eV.Tandem mass spectrometry (MS/MS) data were acquired by using the data-Independent acquisition in both in negative and positive ion modes.Instrument control, data acquisition and processing were performed using Xcalibur soware package (Thermo Fischer Scientic, San Jose, CA, USA).

LC-MS-based data processing and multivariate statistical analysis
LC-MS/MS data processing was performed using Mass Spectrometry-Data Independent Analysis (MS-DIAL) soware. 20he following parameters were used: MS and MS/MS tolerance of 0.01 and 0.05 Da, respectively, retention time = 2-17 min, MS mass range = 50-1500 Da, minimum peak height = 1 × 10 3 amplitude and retention time tolerance of 0.25 min.Post MS-DIAL data processing, the GNPS export les were imported into the GNPS platform using the WinSCP server. 21The GNPS feature processing was achieved following specic parameters such as a fragment ion mass tolerance of m/z (0.25 Da), a minimum number of common fragment ions (5), and a minimum cosine score (0.7).Subsequently, a search of the bronze spectral library was conducted, with the top 10 hits per spectrum.Metabolomic data analysis and interpretation were performed using MetaboAnalyst. 22The resulting data matrix (.csv le) was directly imported to the Metaboanalyst 5 platform (https://www.metaboanalyst.ca/).The dataset was then paretoscaled and log 2 transformed to standardize variables and minimize redundancy.Subsequently, the data was subjected to different statistical analysis methods, including principal component analysis (PCA) and hierarchical cluster analysis (HCA), as unsupervised methods, next to Partial Least Squares Discriminant Analysis (PLS-DA) as a supervised method.The chemical proles of the ethyl acetate extracts from the red alga C. officinalis, and associated Aspergillus.species (A.avipes, A. avus and A. nidulans) were analyzed by LC-ESI-HRMS analysis which was achieved using alternating full scan (FS) and all ion fragmentation (AIF) modes in positive (+) and negative (−) modes.Representative chromatograms are shown in Fig. 1.In total 76 compounds were annotated based on retention times, accurate mass, fragmentation pattern using the available literature [23][24][25] as well as the MS/MS databases and bioinformatics analysis using GNPS 21 (Tables 1 and S1 †).The annotated compounds included 11 polyketides, 8 anthraquinones, 12 alkaloids, 5 peptides, 4 sesquiterpenes, 3 butrylactone derivatives, 2 benzophenone derivatives, 4 fatty acids, 2 quinones, 3 amino acids, 7 carboxylic acids and 15 miscellaneous compounds (Fig. 1).

Results and discussion
An example description of the workow used for annotation of metabolites is described here showing ferulic acid.The identication of ferulic acid was achieved in both negative and positive electrospray ionization modes by the MS 2 analysis (Fig. 2).In negative ionization mode, a molecular ion peak was observed at m/z 193.04830 equivalent to the deprotonated adduct [M − H] − with the chemical formula C 10 H 9 O 4 − .Characteristic product ion fragments were observed at m/z 178.02520 (loss of CH 3 from the precursor ion), m/z 176.0450 (loss of OH from the precursor ion), m/z 149.05910 (loss of CO 2 from the precursor ion) and m/z 134.03620 (loss of CH 3 with CO 2 from the precursor ion). 26,27In positive ionization mode, a molecular ion peak was observed at m/z 195.06730 equivalent to the protonated adduct [M + H] + with the chemical formula C 10 H 11 O 4 + .Characteristic product ion fragments were observed at m/z 180.04380 (loss of CH 3 from the precursor ion), m/z 177.05580 (loss of water from the precursor ion), [M + H-H 2 O] + , and m/z 147.04610 (loss of OCH 3 and OH from the precursor ion). 28Other example description for the annotated metabolites are described in the detailed classication in the following sections.
3.1.1.Polyketides.Polyketides include a diverse array of natural products with different structural skeletons, however, they all share in common their origin from the assembly of acetate/malonate units over PKS (polyketide synthase enzyme complex); anthraquinone and polyketide alkaloids are subclasses of polyketides characterized by a tricyclic anthraquinone core structure as well as nitrogen containing compounds, respectively. 29Polyketides represented the major class of metabolites identied in the studied algae and their three endophytes with a total number of 11 compounds iden-tied in the three species.Emericellamide A ( 57 6 with [M + H] + m/z 539.3798 followed by continuous cleavage of different amide bonds and loss of different amino acid fragments occurred to this moiety till it reaches the last fragment. 30Polyketides were the major secondary metabolites exhibited by the data extracted from LC-MS, where, terrein (4), epicoccolide B (35), curvularin (38), emericellamide A (57), emericellamide E (61) and hormonemate F (66) were detected at different retention times in both negative and positive ionization modes.Compounds 4 was identied as terrain, 24 it showed [M − H] − at m/z 153.05495 with characteristic fragments through the loss of C 2 H 6 unit ([M − H] − -30) 123.0442 and loss of H 2 O ([M − H] − -18)135.0442.Polyketides were the major secondary metabolites exhibited by the data extracted from LC-MS, with total number of 11 where, 6 of which were found in the host algal sample and its three endosymbiotic fungi such as terrein (4) (t R 5.09 min), sterigmatocystin hemiacetal (24) (t R 9.02 min), sterigmatocystin (28) (t R 9.39 min), 5-methoxydihydrosterigmatocystin (36)  were not detected in Aspergillus avus extract, while they were detected in the other three extracts.Acyl-hemiacetal sterigmatocystin (45) (t R 12.74 min), was not identied in the host algal extract and its endosymbiotic A. avipes, while was detected in A. avus and A. nidulans extracts.Emericellamide A (57) (t R 13.92 min), was not detected in A. avipes extract, while was detected in the remaining three sample extracts.
3.1.2.Anthraquinones.Anthraquinones are a subclass of polyketide natural products demonstrating a wide range of biological activities and possible industrial application including cytotoxic, antiplasmodial, anticancer, antitumor, algaecide, antifungal, enzyme-inhibiting, antiplatelet aggregation, antibacterial, antiviral, and phytotoxic properties.3.1.3.Alkaloids.Alkaloids demonstrate distinctive structural skeletons derived from different amino acids.These nitrogen containing compounds are among the most effective compounds, and many of them had been developed into market drug product, still many others under different phases of clinical trials. 33,34Sinapine ( 9) is an alkaloid that is more stable in negative ionization mode therefore the identication was conducted in positive mode to verify ion breakdown.In positive mode of ions, the molecular ion peak [M] + appeared at m/z 310.16489 (Fig. S2 †).Sinapine was fragmented to yield product ion at m/z 251.0912 by loss of trimethyl amine moiety, then loss of ethoxy group to produce m/z 207.0651, followed by loss of two methoxy groups to produce m/z 147.0421, and then loss of hydroxyl group to produce m/z 131.9743 from the precursor ion. 35A total of 12 alkaloids were detected, 8 of which were found in the host algal sample and the three endosymbiotic fungi (A.avus, A. nidulans and A. avipes), such as sinapine (9) (t R 5.63 min), cichorine (15) (t R 6.92 min), aspoquinoline C (39) (t R 11.96 min), cytochalasin Z17 (40) (t R 12.12 min), cytochalasin Z8 (43) (t R 12.67 min), cyclopiazonic acid (55) (t R 13.72 min) (Fig. S3 †) and versiquinazoline J (76) (t R 16.22 min).On the other hand, dethiosecoemestrin (41) (t R 12.35 min) (Fig. S4 †), was only observed in A. nidulans extract and not observed in the host algal extract, A. avus and A. avipes.Emestrin (42) (t R 12.58 min), was observed in A. avus and A. nidulans, whereas, not observed in A. avipes and the host algal extract.Speradine D ( 14) (t R 6.92 min) was only not observed in A. avipes, whereas was observed in A. avus, A. nidulans and the host algal extract.Versiquinazoline E (32) (t R 9.80 min), was only not observed in A. avus, whereas observed in A. nidulans, A. avipes and the host algal extract.
3.1.8.Benzophenone, sesquiterpene and quinone derivatives.Monodictyphenone (54) (t R 13.49 min), was only not detected in the host algal sample extract, while detected in the remaining extracts.On the other hand, arugosin G (74) (t R 15.65 min), was detected in all sample extracts.Four sesquiterpenes were identied, three of them including aspergilloid C (30) (t R 9.70 min), aspergiterpenoid A (34) (t R 10.02 min) and sydonic acid (56) (t R 13.76 min) were detected in A. avus, A. nidulans, A. avipes and the algal extracts.On the other hand, insulicolide A (7) (t R 5.33 min) was not detected in A. avus and A. nidulans extracts, while detected in A. avipes and algal extracts.
Two quinone derivatives were identied.Erythroglaucin (25) (t R 9.20 min), was only not detected in the host algal extract, whereas detected in A. avus, A. nidulans and A. avipes extracts.On the other hand, avoglaucin (67) (t R 14.35 min) was detected in all four sample extracts.
The comprehensive metabolomic study of the three different Aspergillus sp.revealed that polyketides, anthraquinoes and alkaloids are the major classes of the identied secondary metabolites.][44] Moreover, the presence of common compounds in the host algae C. officinalis as well as the three isolated Asprgillus endosymbionts unveils the presence mutualistic symbiotic relationship emphasizing the ecological signicance the fungal endophytes, where they can provide bioactive metabolites as chemical defense strategy to the host organism and in turn secures a nutrient rich system to ourish.

Multivariate analysis of the LC-ESI-HRMS data
Non-targeted metabolomics approaches based on liquid chromatography-high resolution mass spectrometry (LC-HRMS) have been widely used for specic discrimination of different biological samples particularly from plants and fungi. 83,84Chemometrics tools such as principal component analysis (PCA), hierarchical clustering analysis (HCA) and partial least squares discriminant analysis (PLS-DA) provide avipes while the second cluster revealed separation of A. nidulans from A. avus and C. officinalis, consistent with PCA results (Fig. 4B).Heatmap of the top 30 metabolites differentially changing between C. officinalis and associated endosymbiotic Aspergillus fungi is depicted in Fig. 5.
Supervised classications, on the other hand, including partial least squares discriminant analysis (PLS-DA) was used as multivariate dimensionality-reduction tool for discriminative variable selection (Fig. 4C).PLS-DA achieved the effective discrimination between the tested groups.A Variable Importance for Projection (VIP) score is a measure of a variable importance in the PLS-DA model.It summarizes the quantitative contribution of a variable to the model.The candidate metabolites with variable importance in the PLS-DA (VIP) responsible for the discrimination and with scores $1 were considered important in the PLS-DA model (Fig. 4D).Anthraquinones such as eurotinone, 2-methyleurotinone and 6,8-O-dimethylaverantin were found to be discriminatory metabolites for A. avipes.Additionally, polyketides such as epicoccolide B, monodictyphenone and hormonemate F as well as other xanthones derivatives such as sterigmatocystin, sterigmatocystin hemiacetal and 5-methoxydihydrosterigmatocystin inuence the metabolic discrimination of A. avipes from Corallina officinalis and other associated endosymbiotic Aspergillus fungi (A.avus and A. nidulans).Further, alkaloid derivatives such as sinapine, cyclopiazonic acid and versiquinazoline (J) together with fatty, benzoic and amino acids derivatives (e.g.N-acetyl- leucine, phenylalanine, 2-(((2-Ethylhexyl)oxy)carbonyl)benzoic acid, 8-Hydroxy-9,12-octadecadienoic acid, 7-hydroxy-8,14dimethyl-9-hexadecanoic acid and glycerol linoleate) dominated A. avus.Additionally, penidiamide, curvularin and aspergilloid C were found to discriminate this fungal species.Moreover, metabolites from diverse chemical classes such as cichorine, aversin, violaceol I, nidulol, alternariol and emericellamide E were found to be abundant in A. nidulans, discriminating it from C. officinalis and other associated endosymbiotic Aspergillus fungi.C. officinalis was found to accumulate avoglaucin, emericellamide E, daidzein, orsellinic acid next to some fatty acids and organic acid derivatives.

Conclusions
In this study, we investigated the metabolic prole of C. officinalis and the three isolated endophytes A. nidulans, A. favipes, and A. avus using LC-MS/MS.C. officinalis and its endosymbiotic fungi demonstrate a valuable source of various metabolites including alkaloids, polyketides, sesquiterpenes, butyrolactones, peptides, fatty acids, isocoumarins, and quinones.Based on LC-MS/MS, polyketides represented the highest percentage (14%) among other metabolite classes of C. officinalis and related endosymbiotic Aspergillus fungi, followed by alkaloids (13%), anthraquinones (11%), peptides (7%), fatty acids and sesquiterpenes (5% for each one), in addition to small amounts of other classes such as butyrolactones, diketopiperazines, isocoumarins, amino acid derivatives, benzoic acid derivatives, and other miscellaneous classes.All metabolites that were found in C. officinalis were also exist in its endophytes with different proportions.On the contrary, some metabolites have been identied in endosymbiotic fungi and did not exist in their host.The chemical proling of many groups of algae and their endophytes is still unrevealed and needs to be explored.These ndings will be of interest in pharmaceutical applications for drug discovery from natural resources.Further studies also should be pushed toward investigating the correlations

3. 1 .
Chemical proling of the red alga C. officinalis, and associated Aspergillus sp.
) is a polyketide identied in positive ionization mode and showed [M + H] + molecular ion peak at m/z 610.41785 with chemical formula C 31 H 56 N 5 O 7 + .Emericellamide A fragmentation mechanism in the positive ion mode starts by loss of fragment ion [M + H] + m/z 71.04 with the chemical formula C 3 H 5 NOc and the remained moiety was C 28 H 51 N 4 O $ 31,32 HR-LC-MS analysis revealed the predominance of anthraquinones in the algal extracts and the three endosymbiotic fungi.2-Methyleurotinone(60), is an anthraquinone compound that showed [M − H] − peak at m/z 301.0718, 286.0485, 271.0252, and 243.0300, respectively in negative ionization mode.2-Methyleurotinone was fragmented in MS 2 analysis to yield product ion at m/z 286.0485 by loss of OH, m/z 271.0252 by loss of OCH 3 , and m/z 243.0300 by loss of CO 2 and CH 3 from the precursor ion.A total of 8 anthraquinone derivatives were detected, 5 of which were found in the host algal sample and its three endosymbiotic fungi such as asperavin (12) (t R 6.60 min), 2-O-methyl-9dehydroxyeurotinone (18) (t R 7.97 min), emodin (52) (t R 13.49 min) (Fig.S1 †), 2-methyleurotinone (60) (t R 14.08) and 6,8-Odimethylaverantin (64) (t R 14.25 min).Also, the other three metabolites, 5-hydroxyaverantin (3) (t R 4.17 min), eurotinone (53) (t R 13.49 min) and aversin (69) (t R 14.56 min) were detected in the three endosymbiotic fungi and totally absent in the host algal sample.

Fig. 1
Fig. 1 Chemical profiling of the red alga C. officinalis, and endosymbiotic Aspergillus fungi extracts.Total ion chromatograms (TIC) of metabolites measured by UPLC-MS-MS in negative (A) and positive (B) ionization modes.Percentages of the different classes of annotated metabolites (C).

Fig. 2
Fig. 2 Total ion chromatogram (TIC) and extracted ion chromatograms (EIC) of the peak representing ferulic acid measured by UPLC-MS-MS in negative (A) and positive (B) ionization mode from A. nidulans extract.

Fig. 4
Fig. 4 Multivariate statistical analysis of liquid chromatography-high resolution mass spectrometry (LC-HRMS) data of C. officinalis and associated endosymbiotic Aspergillus fungi.Principal component analysis (PCA) score plot (A), hierarchical cluster analysis (HCA) dendrogram (B), Partial Least Squares Discriminant Analysis (PLS-DA) score plot (C) and variable importance in projection (VIP) scores of the top 15 significant metabolites (D).

Fig. 5
Fig. 5 Heatmap of the top 30 metabolites differentially changing between C. officinalis and associated endosymbiotic Aspergillus fungi based on the results derived from the liquid chromatography-high resolution mass spectrometry (LC-HRMS) data.All metabolites presented here have p < 0.05 based on ANOVA results and a fold-change> 2.

Table 1
Annotated metabolites in the ethyl acetate extracts of the red alga, C. officinalis, and associated endosymbiotic fungi namely, A.

Table 1 (
Contd. ) (t R 6.43 min) and fellutamide D (51) (t R 13.45 min) were detected in all four extracts.Emericellamide C (50) is a peptide identied in positive ionization mode and showed [M + H] + molecular ion peak at m/z 596.4021with chemical formula C 30 H 54 N 5 O 7 + .Emericellamide C fragmentation mechanism in the positive ion mode starts by loss of fragment ion [M + H] + m/z 71.04 with the chemical formula C 3 H 5 NOc and the remained moiety was C 27 H 49 N 4 O $ 6 with [M + H] + m/z 525.3638 witnessed continuous cleavage of different amide bonds and loss of different amino acid fragments to produce different product ions including 454.3265, 341.2424, and 244.1647.
). Orsellinic acid (1) (benzoic acid derivative) showed molecular ion [M − H] − peak at m/z 167.03418 with the chemical formula C 8 H 7 O 4 − in negative electrospray ionization mode.Characteristic product ion fragments were observed at m/z 151.0393 (loss of OH from the precursor ion), and m/z 123.0443 (loss of carboxylic group from the precursor ion). 38,39Also two identied phenyl acetic acid derivatives were observed in all examined extracts, including p-hydroxyphenyl acetic acid (2) (t R 4.14 min) and homogenentisic acid (21) (t R 8.66 min).3.1.7.Butrylactone derivatives.Butyrolactone VII (47) (benzoic acid derivative) showed molecular ion [M + H] + peak at m/z 439.1755 with the chemical formula C 25 H 27 O 7 + in the positive electrospray ionization mode.Characteristic product ion fragments were observed at m/z 422.2278 (loss of OH from the precursor ion), m/z 331.1309 (loss of two OH groups and C 3 H 5 O $ 2 from the precursor ion), and m/z 175.1107 (loss of C 13 H 11 O $ is an isocoumarin that showed molecular ion [M − H] − peak at m/z 271.0612 with the chemical formula C 15 H 11 O 5 − in negative electrospray ionization mode.The main product ion fragment was observed at m/z 228.0429 (loss of CO 2 from the precursor ion). 41Two compounds belong to isocoumarin derivatives, Alternariol monomethyl ether (22) (t R 8.69 min) and alternariol (37) (t R 10.87), were totally not detected in the host algal sample extract, while were detected in A. avus, A. nidulans and A. R 14.25 min) (Fig. S10 †), was only detected in both A. nidulans and A. avipes extracts, while this metabolite was totally not detected in A. avus and the algal extracts.On the other hand, the rest of different categories of identied miscellaneous metabolites were detected in all examined sample extracts such as, kojic acid methyl ether (6) (t R 5.20 min) belongs to gamma-pyrone derivatives, orsellinaldehyde (8) (t R 5.45 min), 180.0412 (loss of CH 3 from the precursor ion), m/z 151.0386 (loss of CO 2 group from the precursor ion), and m/z 147.0437 (loss of methoxy and OH groups from the precursor ion).Violaceol I (31) is a diphenyl ether with molecular ion [M + H] − peak at m/z 261.0773 and chemical formula of C 14 H 13 O 5